Format Customization: The Impact of Info Presentation Format and Consumer’s Learning Style on Communication Efficiency and Purchasing Decision

This research review information acquisition and analysis processes in both marketing and education literature and will empirically test the applicability of the VAK (visuals, auditory, kinesthetic/tactile) perceptual learning styles model to customize online info presentation format. This is performed by studying the effect of matching distinct online presentation formats with consumers’ learning style on communication efficiency and purchasing decision. A 3(visual-rich, auditory-rich, and interactive/simulation-rich for online presentation format)X 3(visuals, auditory, kinesthetic/tactile for consumer’s learning style) experiment is under development. While the purpose of experiment is to test for presentation format and learning style congruency effect on communication efficiency and purchasing decision and present a reliable scale for consumer perceptual learning styles, it would also reveal a potential superiority of one format for the general population, i.e. indifferent learning style, and enable to verify specific response patterns, i.e. for individuals with two prevalent learning styles, for kinesthetic/tactile individuals. Communication efficiency will be measured by memory recall and website assessment; purchasing decision is reflected by product evaluation time, perceived purchase risk and intention to buy. Different product categories with different complexity and tangibility levels are included at the simulated site to reduce product-characteristics effect and allow for generalizability of findings. Research in mass customization and personalization has so far stressed production and technology aspects of the process. While some studies have showed how customizing item locations at a certain media, i.e. customized email, based on consumers’ observed behaviour or preferences can enhance communication efficiency or productivity (Ansari, 2003), other research in online behaviour have concentrated on modeling and predicting online consumer and shopping behavior (Montgomery, Srinivasan, Li and Liechty, 2004; Sismeiro and Bucklin, 2004; Kalczynski, Senecal, and Nantel, 2006), showing that models could be useful in predicting behavior based on current status, demographics, visit sequence and clickstream. Consumer research has shown that differences in consumers predict where and how a consumer chooses to shop and be motivated to behave in a certain way (Roth, 1997). Internet technology has been advancing rapidly making it possible to provide a personalized webpage, in both content and format, for each